Sentiment Analysis of Political Tweets

Abstract

Social media has proven rapid growth in becoming the most popular activities in internet and to appeal the researchers to get better insights into the understanding of the underlying sociology. In olden days traditional form of navigation and hypertext browsing was used which is now replaced by tags (used in twitter) and it is less time consuming. Twitter is one popular web application nowadays. Twitter allows users to use hash tags to extract only those tweets related to a particular category. Twitter is called a micro-blog because anyone can post short messages up to 140 characters in length. We use our past experiences when we make decisions such as to take various selections in our everyday life whilst buying, making an investment money, handling others, deciding on our favourite celebrity, celebrities, electing our ministers. It was quoted by somebody “who learns from his own mistakes is smart, but who learns from others mistake is genius”. Sentiment analysis enables us to use others past experiences to make right decisions. In sentiment analysis we collect reviews from social networks, in my project I extracted from twitter, and analyse these reviews in a way that can convey us the writer’s opinion, which will help us in making plans in future. Sentiment analysis is a challenging task because to do the analysis it requires a deep knowledge of implicit and explicit, we need to consider the regular and irregular express-ions and grammatical rules of the language. My project is based on politics; Sentiment Analysis can help the political parties when they make future policies, their party promotion and is also helpful in predicting the election results. As soon as the time for election start people also begin sharing their opinion on social networking sites and these sites during peak time of election gets flooded with the online discussions about political parties, candidates representing the parties, bunches of disputable discourses and level headed discussions are held over social networks. And when people share thoughts and discuss, it give us opportunity to use these as a resource for study and analysis. In our research we are using twitter as our data source and we are applying lexical approach of sentiment analysis. In Lexical approach it works on bag of words to extract the sentiments, it considers each word in a sentence and these words are matched with pre-set dictionary words.